Analysis of the architecture of a remote-controlled vehicle and automatic label localization

Abstract

This thesis presents the design and evaluation of a cost-constrained, remote-controlled vehicle architecture for automatic label localization and inventory registration in outdoor metallic yards. The proposed system combines high-resolution vision, RFID, GPS and ultrasonic sensing on a rocker-bogie mobile platform, using vision as the primary modality to detect and read deteriorated labels while RFID acts as an assistive channel to confirm presence and recover IDs when visual information is incomplete. A three-stage methodology is followed: (i) characterization of a baseline teleoperated system, (ii) redesign of sensing, power, and logging to obtain reliable multimodal records, and (iii) implementation of a semi-autonomous detection-search-tracking-registration loop coordinated by a lightweight state machine. Across these stages, the architecture evolves from manual data capture with fragmented logs to a unified registration model in which each event bundles image, EPC/ID, GPS-based yard zone and quality indicators, locally stored and streamed to a cloud dashboard via MQTT for real-time supervision. Field tests in realistic yard conditions show that the final system can reduce typical time-to-register per label, increase data completeness and GPS-based localization quality, and lower operator workload by shifting effort from manual scanning to high-level supervision. The results demonstrate that a low-cost, vision-first, RFID-assisted vehicle can significantly improve traceability and safety in outdoor inventory operations.